Triple

T17906070
Position Surface form Disambiguated ID Type / Status
Subject Powerpuff Girls Z E447702 entity
Predicate featuresCharacter P626 FINISHED
Object Ken Kitazawa
Ken Kitazawa is a supporting character in the anime series "Powerpuff Girls Z," known as a young scientist who helps the Powerpuff Girls with his inventions and technological expertise.
E2291016 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ken Kitazawa | Statement: [Powerpuff Girls Z, featuresCharacter, Ken Kitazawa]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ken Kitazawa
Triple: [Powerpuff Girls Z, featuresCharacter, Ken Kitazawa]
Generated description
Ken Kitazawa is a supporting character in the anime series "Powerpuff Girls Z," known as a young scientist who helps the Powerpuff Girls with his inventions and technological expertise.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8b9f6d394819082a6d69fd1e23d2f completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49e9c7f54819088c6d2ce7bbea073 completed April 19, 2026, 9:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5c1caf2b288190a07d2273dc5deb0d completed July 19, 2026, 12:39 a.m.
NEDg Description generation batch_6a5c1d1f5bd081908e65bb174280c1fa completed July 19, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a5c1d6fab948190b547d69ca7973429 completed July 19, 2026, 12:42 a.m.
Created at: April 10, 2026, 10:19 a.m.